1. Field of the Invention
The present invention relates to image processing and in particular to image processing techniques whereby image artefacts produced during image acquisition are corrected for in the generation of an output image.
2. Discussion of Prior Art
Magnetic Resonance Imaging (MRI) is a widely used technique for medical diagnostic imaging. In a conventional MRI scanner, a patient is placed in an intense static magnetic field which results in the alignment of the magnetic moments of nuclei with non-zero spin quantum numbers either parallel or anti-parallel to the field direction. Boltzmann distribution of moments between the two orientations results in a net magnetisation along the field direction. This magnetisation may be manipulated by applying a radiofrequency (RF) magnetic field at a frequency determined by the nuclear species under study and the strength of the applied field. In almost all cases, the species studied is the nucleus of the hydrogen atom, present in the body mainly in water molecules, and RF pulses are applied at the resonant frequency of these water protons.
The energy absorbed by nuclei from the RF field is subsequently re-emitted and may be detected as an oscillating electrical voltage, or free induction decay (FID) signal in an appropriately tuned antenna. More commonly, a further RF pulse, or magnetic field gradient, is used to postpone signal acquisition and generate a spin-echo or gradient-echo signal.
Spatial information is encoded into the echo signal by virtue of additional linearly varying magnetic fields, known as magnetic field gradients, applied during or prior to echo acquisition. The principle of spatial encoding is that in the presence of the field gradient, the net field experienced by a given nuclear moment, and hence its resonant frequency, is a function of position within the scanner. When a gradient is applied during the echo acquisition, the received signal contains a range of frequency components representing nuclei at different locations along the gradient direction. Fourier transformation of this signal yields a one-dimensional projection through the patient. This technique is known as frequency encoding. Two-dimensional encoding requires use of an additional gradient applied perpendicular to the frequency encoding axis, known as the phase encoding gradient. This gradient is applied for a short time prior to data acquisition. The acquisition process is repeated perhaps 256 or 512 times using phase encoding gradients of different strengths. Simultaneous frequency and phase encoding yields a two-dimensional data set which when subjected to two-dimensional Fourier transformation provides the required image. This array of data exists in what is known as k-space and is the Fourier transform of the image space. The effect of the phase encoding gradient is to move the start of the data acquisition to a particular location along one axis in k-space (dependent on the gradient strength), whilst frequency encoding represents a sweep through k-space parallel to the other axis. Each of these sweeps is known as a xe2x80x9cshotxe2x80x9d or xe2x80x9cviewxe2x80x9d.
Spatial localisation in the third dimension may be achieved using an additional phase encoding gradient, or more commonly by using a gradient and narrowband RF pulse to restrict the initial perturbation of nuclear moments to a single tomographic slice. This principle can readily be extended to multislice MRI.
In conventional MRI, a single phase-encoding view is acquired after each RF excitation. However, faster imaging sequences now exist in which further RF pulses and phase encoding gradients are used to acquire a train of differently encoded echoes after each excitation. These echoes traverse several lines of k-space and reduce scanning time by a factor equal to the echo train length. In the extreme case, single shot echo planar imaging (EPI) techniques cover the whole of two dimensional k-space in a single acquisition lasting less than 100 ms, although spatial resolution and image quality may be significantly compromised.
Patient movement during the acquisition of MRI images results in degradation of the images that can obscure the clinically relevant information. Each readout period takes a few milliseconds (ms), whereas the time interval between readouts might be between 500 and 2000 ms. The majority of blurring and ghosting artefacts caused by patient motion are due to motion between lines in k-space, rather than motion during a single readout.
Movement leads to phase errors between lines of k-space, which in the resulting image appear as blurring and ghosting along the phase encode direction. These phase errors can result from translations and rotations. Translations of the patient in the readout direction result in a frequency dependent phase shift in each line of k-space. Rotations in the spatial domain are also rotations in k-space, and result in a phase shift that is a more complicated function of position.
A particular type of MRI image investigation, known as diffusion weighted imaging, takes place in the presence of an additional and separate gradient. The integral over time of the diffusion weighted gradient is greater than the integral for the phase encode or readout gradients. The purpose of this additional gradient is to make the images sensitive to molecular motion of the order of 10 xcexcm. A side effect is that the images are also sensitive to bulk motion on the same scale. Anderson et al. in Magn. Reson. Med. Volume 32, 1994, pages 379-387 have shown that for small rigid body movements, the resulting artefacts can be modelled using zero and first order phase correction terms.
Considerable work has been done by MR researchers to model patient motion, and to attempt to correct for it. The impact of different types of motion on the resulting images is well understood, but clinically usable retrospective motion correction techniques are not yet available. Existing algorithms tend to correct only for one dimensional motion, or they require exotic image acquisition strategies that are not generally applicable.
There are broadly two classes of movement correction algorithm used in MRI; with and without xe2x80x9cnavigator echoesxe2x80x9d. Motion correction using additional echoes referred to as xe2x80x9cnavigator echoesxe2x80x9d involves the acquisition of additional echoes that are not phase encoded between each phase encoded echo. All navigator echoes are projections through the object. It is therefore possible to measure motion between the navigator echoes, and consequently infer the motion between the corresponding phase encoded echoes. The navigator echoes are most commonly used to measure motion in one or more translational directions. Published papers describing the use of navigator echo techniques include that of Ehman et al. in Radiology, Volume 173, 1989, pages 255 to 263. Recently several authors have proposed obtaining rotational information either from these straightforward navigator echoes, for example Anderson et al. in Magn. Reson. Med. Volume 32, 1994, pages 379-387, or from circular navigator echoes for example Fu et al. in Proc. Soc. Magn. Reson., 1994, page 355.
There have been attempts to measure movement directly from the phase encoded data. Felmlee et al., as reported in Radiology, Volume 179, 1991, pages 139 to 142 tried to measure translations directly from a hybrid space comprising the Fourier transform of the readout vs. phase encode, but found that it worked for phantoms with high spatial frequency edges, but on human subjects only if high contrast markers were used. A possible solution to this is to acquire spiral readouts, all of which sample a range of spatial frequencies as described by Khadem et al. in Proc. Soc. Magn. Reson., 1994, page 346, but this is impractical on the majority of MRI hardware. An alternative strategy described by Wood et al. in J. Magn. Reson. Imag., Volume 5, 1995, pages 57 to 64, is to locate discontinuities in k-space that correspond to sudden movements of the patient, to split the regions of k-space between these discontinuities into sub-images, then to correct for translations by applying a phase shift to k-space, and rotations by rotating in the spatial domain. This technique cannot correct for continuous movement during acquisition, and would appear to require considerable user interaction.
An alternative approach to motion correction without navigator echoes is the Projection Onto Complex Sets (POCS) technique described by Hedley et al. in IEEE Trans. Med. Imag., Volume 10, 1991, pages 548 to 553 and extended by Gmitro et al. in xe2x80x9cInformation Processing in Medical Imaging, ed. Bizais, Barillot, Paola, Iles de Berder, Kluwer, 1995. This has been proposed as a means of correcting for motion during diffusion weighted imaging of the brain.
In the implementation used by Gmitro, the constraint in the image domain is provided by an image acquired without any diffusion weighting gradient (the reference image). Correction is performed in hybrid space (x vs. Ky), under the constraint that the magnitude and higher-order phase terms of each line are correct.
A binary mask is generated from this reference image (spatial domain), in which pixels inside the head are given the value 1, and pixels outside the head the value 0. This constraint is applied to the corrupted images by multiplying the image by the mask function. The resulting product image has a black background, and consequently lacks the ghosting artefacts outside the head that are caused by motion. This masked image is then transformed into hybrid space, and is compared, line by line, with the hybrid space of the original (unmasked) image. The zero and first order phase terms that, when applied to the original hybrid space lines, produce the closest match (in a root mean square sense) to the lines of the hybrid space from the masked image are then found using a search procedure. These phase terms are then treated as estimates of the motion correction parameters, and the algorithm reiterates.
In general, a mask image as required by this algorithm, may not be available, or may be out of registration with the images that need correction, and thus inaccurate.
The use of averaging or correlation to smooth out motion artefacts has been described in U.S. Pat. Nos. 5,363,044, 5,233,302, 5,124,649, and 4,966,149. The correction of image data using motion information derived from the image data or from extra motion detection or position tracking sequences is described in U.S. Pat. Nos. 5,427,101, 5,382,902, 5,254,948 and 5,251,128 and in Japanese Pat No 05080248. U.S. Pat. No. 5,311,132 describes correcting demodulation frequency in an MRI imaging process using a focusing criterion to determine image blur.
The technique described in U.S. Pat. No. 5,363,044 requires the acquisition of two interleaved data sets. These data sets are combined into a single image. The image is divided into sub-sections and a xe2x80x9cgradient energyxe2x80x9d term is summed over all the pixels of each sub-section of this image. The gradient energy term is defined as the sum over all the pixels of the total of the squares of four partial derivatives of the real and imaginary parts of a complex image, with the partial derivatives being the difference between an image and the image shifted by one pixel. A phase term used in the data combination is varied until the gradient energy sum in each sub-section is minimised. This technique determines a phase factor which locally removes ghosts in an image. The phase factor depends on the interleave conditions and the harmonic number of the motion. It assumes that the motion is periodic or quasi-periodic with respect to the acquisition order. It is likely that to be effective, this technique requires the image to be sub-divided into regions. where the ghosts do not overlap either each other or the main body of the image and therefore its applicability is limited.
U.S. Pat. No. 5,311,132 describes a technique for correcting magnetic resonance images by removing blur introduced as a result of magnetic field inhomogeneities and variations in magnetic susceptibility of an object being imaged. It does not correct for artefacts due to motion. The technique described therein involves demodulating acquired data at different frequencies to overcome such blurring. Using a local focus criterion, the demodulation frequencies which optimise the focus of each region of an image are determined. Compensating for magnetic field inhomogeneities is significantly less complex than correcting for motion artefacts. Only one parameter needs to be searched for at each image region. Correction for motion artefacts is more complex because motion affects the focus in all regions and in general there are six degrees of freedom rather than one for field inhomogeneities. The technique is applicable only to non-Fourier transform reconstruction techniques.
It is an aim of the present invention to provide an alternative method for processing signals generated by a magnetic resonance imaging machine to generate an image such that image defects arising from patient motion during the acquisition of the signals are corrected for in a manner which does not require a modified signal acquisition technique.
The present invention provides a method for generating an artefact reduced physiological image of an object comprising the steps of:
(i) acquiring a data set from a plurality of received signals generated in an object measuring process;
(ii) manipulating the data set in order to generate an image therefrom, wherein the data set manipulation includes the reduction of image artefacts resulting from object motion during said object measuring process,
characterised in that the data set manipulation step includes the stages of:
(a) calculating a focus criterion for an initial artefact containing image;
(b) generating an initial model for the motion of the object during the object measuring process;
(c) manipulating the data set in order to compensate for the effects of the model and recalculating the focus criterion for the manipulated data set; and
(d) iteratively varying the model and repeating stage (c) in order to obtain a final object motion model with which the focus criterion is optimised;
wherein the artefact reduced image is then generated from the data set after the data set has been manipulated in order to offset the effects of the final object motion model.
The invention provides the benefit of providing a method whereby the image quality of certain images which are distorted by motion of the object during data acquisition may be improved.
The method of the invention is particularly applicable for manipulating images obtained using magnetic resonance imaging (MRI) techniques. Preferably the focus criterion is an image entropy criterion. The term image entropy is taken here to mean the degree of disorder in an image.
Patient motion in MRI scans may be in directions known as the readout direction and the phase encode direction. The data set may be manipulated to reduce the effect of patient motion in these directions. In addition, rotation motions may be corrected.
An image entropy criterion may be taken over the whole of an image or it may be determined for specific regions of an image. For example in an MRI image of a head, the image entropy may be calculated for only for those regions of the whole image in which the patients head is imaged.
Several techniques for varying the model of patient motion may be used. The patient motion model may be varied in a piecewise linear or piecewise constant manner. In more sophisticated techniques segments of the patient motion curve are varied with the size of the segments being reduced as the model is optimised. Alternatively a limited set of nodes of the patient motion curve may be initially varied with more nodes then being varied to obtain a finer scale patient motion curve. It may be desired to initially obtain an image over a limited sub-set of k-space lines, with the focus criterion for this sub-image being optimised before the sub-set is expanded. These techniques might be employed to reduce the time taken to obtain a corrected image.
In a further aspect, the invention provides a method of improving the image quality of magnetic resonance imaging images by the reduction of motion induced artefacts comprising the steps of:
(a) calculating a focus criterion for an initial artefact containing image;
(b) generating a model of a possible motion sequence as a cause of the artefact;
(c) manipulating the data set in order to compensate for the effects of the model and recalculating the focus criterion for the manipulated data set; and
(d) iteratively varying the model in order to obtain a final model with which the focus criterion is optimised;
wherein the artefact reduced image is then generated from the data set after the data set has been manipulated in order to offset the effects of the final model.
Compared with prior art techniques for MRI image improvement where a specialised image acquisition strategy has to be adopted, this aspect of the invention provides the advantage that a conventional imaging process may be used which is then followed by a post-acquisition processing stage.
In another aspect, the invention provides a magnetic resonance imaging scanner arranged to generate an artefact reduced image of a patient by performing the steps of:
(i) acquiring a data set from a plurality of received signals generated in a patient measuring process;
(ii) manipulating the data set in order to generate an image therefrom, wherein the data set manipulation includes the reduction of image artefacts resulting from patient motion during data acquisition,
characterised in that the data set manipulation step includes the stages of:
(a) calculating a focus criterion for an initial motion artefact containing image;
(b) generating a patient motion model as a possible cause of the artefact;
(c) manipulating the data set in order to compensate for the effects of the model and recalculating the focus criterion for the manipulated data set; and
(d) iteratively varying the model in order to obtain a final model with which the focus criterion is optimised;
wherein the artefact reduced image is then generated from the data set after the data set has been manipulated in order to offset the effects of the final model.
Subsequent to the filing of the priority application, a scientific paper by R. A. Zoroofi, Y. Sato, S. Tamura and H. Naito was published in IEEE Transactions on Medical Imaging, Vol. 15, No. 6, December 1996, pages 768-784, relating to MRI artefact cancellation due to rigid motion in the imaging plane. The paper concerns blurring and ghosting due to motion during the image acquisition. The technique described therein involves using a minimum energy method to estimate unknown motion parameters. The minimum energy method requires a knowledge of the boundary of a region of interest whereas an entropy focus criterion does not require knowledge of any boundary position. The method of Zoroofi et al. is to select a group of k-space lines over which they believe there has been no motion, based on tests which are performed algorithmically, and an image is formed from these lines, thresholded and used as the boundary of the region of interest. In order for the method to be effective it is necessary to be able to identify a group of k-space lines over which there is little motion. The method of the present invention does not have this requirement and can compensate for continuous motion.